Open source geoprocessing tools and meteorological satellite data for crop risk zones monitoring in Sub-Saharan Africa
- Published
- Accepted
- Subject Areas
- Databases, Emerging Technologies, Scientific Computing and Simulation, Spatial and Geographic Information Systems, World Wide Web and Web Science
- Keywords
- crop model, risk zones, Sub-Saharan, PL/pgSQL, Web Services, satellite imagery, WebGis application, food security
- Copyright
- © 2016 De Filippis et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Open source geoprocessing tools and meteorological satellite data for crop risk zones monitoring in Sub-Saharan Africa. PeerJ Preprints 4:e2265v1 https://doi.org/10.7287/peerj.preprints.2265v1
Abstract
In Sub-Saharan Africa analysis tools and models based on meteorological satellites data have been developed within different national and international cooperation initiatives, with the aim of allowing a better monitoring of the cropping season. In most cases, the software was a stand-alone application and the upgrade, in terms of analysis functions, database and hardware maintenance, was difficult for National Meteorological Services (NMSs) in charge of the agro-hydro-meteorological monitoring. The web based solution proposed in this work intends to improve and ensure the sustainability of applications so to support national Early Warning Systems (EWSs) for food security. The Crop Risk Zones (CRZ) model for Niger and Mali, integrated in a web-based open source framework, has been implemented using PL/pgSQL & PostGIS functions to process different meteorological data set: a) the rainfall precipitation forecast images from Global Forecast System (GFS) b) the Climate Prediction Center (CPC) Rainfall Estimator (RFE) for Africa c) MSG images from EUMETSAT Earth Observation Portal d) the MOD 16 Global Terrestrial Evapotranspiration Data Set. Restful Web Services uploads raster images into the PostGIS spatial database for PostgreSQL and PL/pgSQL functions were employed to run CRZ model to identify for the main crops of the Region, the installation phases, the crops phenological phases and risk production zones images. This model is focused on the early identification of risks and the production of information for food security within the time prescribed for decision-making. The challenge and the objective of this work is to set up an open access monitoring system, based on meteorological open data providers, targeting NMSs and any other local decision makers for drought risk reduction and resilience improvement.
Author Comment
“This is an article intended for the OGRS2016 Collection”
SESSION Modelling spatio-temporal processes using open source geospatial tools